Partially calibrated semi-generalized pose from hybrid point correspondences

Snehal Bhayani, Torsten Sattler, Viktor Larsson, Janne Heikkila, Zuzana Kukelova

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

We study the problem of estimating the semi-generalized pose of a partially calibrated camera, i.e., the pose of a perspective camera with unknown focal length w.r.t. a generalized camera, from a hybrid set of 2D-2D and 2D-3D point correspondences. We study all possible camera configurations within the generalized camera system. To derive practical solvers to previously unsolved challenging configurations, we test different parameterizations as well as different solving strategies based on state-of-the-art methods for generating efficient polynomial solvers. We evaluate the three most promising solvers, i.e., the H51f solver with five 2D-2D correspondences and one 2D-3D match viewed by the same camera inside the generalized camera, the H32f solver with three 2D-2D and two 2D-3D correspondences, and the H13f solver with one 2D-2D and three 2D-3D matches, on synthetic and real data. We show that in the presence of noise in the 3D points these solvers provide better estimates than the corresponding absolute pose solvers.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages2881-2890
Number of pages10
ISBN (Electronic)9781665493468
DOIs
Publication statusPublished - 2023
Event23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023 - Waikoloa, United States
Duration: 2023 Jan 32023 Jan 7

Conference

Conference23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023
Country/TerritoryUnited States
CityWaikoloa
Period2023/01/032023/01/07

Subject classification (UKÄ)

  • Computer Vision and Robotics (Autonomous Systems)

Free keywords

  • Algorithms: 3D computer vision
  • Computational photography
  • image and video synthesis
  • Image recognition and understanding (object detection, categorization, segmentation, scene modeling, visual reasoning)

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